To perform efficient scheduling in a heterogeneous multi-core architecture environment, a time during which each task is executed in heterogeneous cores (e.g., a central processing unit (CPU), a graphics processing unit (GPU), a digital signal processor (DSP), and the like) needs to be considered. However, in the heterogeneous multi-core environment, there is no way to measure a duration of a task being executed except for monitoring an operation of the task. Continuously monitoring a duration of every task being executed may be considered, but in this case, excessive overhead may occur.
To address such a problem, in a heterogeneous multi-core architecture environment of the related art, a training run scheme is used to measure a duration of a task being executed. The training run scheme includes executing a program in each of, for example, a CPU and a GPU to store a task execution duration in a database, and assigning the program by referring to the task execution duration stored in the database.
However, the training run scheme merely considers a single-task environment, and thus may not be adaptively used in a multi-task environment.
The above information is presented as background information only to assist with an understanding of the present disclosure. No determination has been made, and no assertion is made, as to whether any of the above might be applicable as prior art with regard to the present disclosure.